Asset Management, GIS and LiDAR Projects

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For most DOTs, knowledge of vertical clearances between the paved roadway surface and vertical structures is an important piece of information that supports the routing of oversized permit vehicles. In addition, horizontal clearances under overhead structures between fixed objects such as bridge columns, railings and median barriers are also important to ensure oversized objects do not impact the structure. Most DOTs use this information for posting clearance signs identifying the vertical clearance of structures and utilize the horizontal clearance information to route oversized vehicles. There are also Federal reporting requirements as part of the National Bridge Inventory (NBI) program that is administrated by FHWA. Many DOTs measure vertical clearances as a single, minimum value under each bridge or overhead structure. This is typically measured by field personnel who are exposed to moving traffic, lane closures and traffic delays, which create safety issues along the road. This manual measurement methodology can also be inaccurate because of the “human factor” involved in making these measurements. The position of the minimum value gets applied to the entire structure, even though it may be in a position that can easily be avoided with proper planning. This methodology can also create situations where a manual measurement methodology may not identify the true minimum clearance because it was missed because of the measurement technology limitations. There are a handful of DOTs in the industry who are using mobile LiDAR technology to inventory their overhead obstructions using mobile LiDAR and right-of-way imagery. This blend of technology is a cost-effective way to precisely measure these clearances while effectively increasing safety for workers and the traveling public. The information gathered here can be used to:

Update the NBI database,

Routing of oversize permit vehicles

Bridge Vertical Clearance Signage

Maintain an Inventory of Overhead Sign and Bridge inventory.

The next set of graphics illustrates the typical technology solution utilized for these projects. It is composed of the Riegl VMX-450 LiDAR unit. This system can collect at rates up to 1.1 KHz (1,100,000 pts/sec) at a precision of 5mm. It collects points in a circular (360-degree) pattern along the right-of-way from 2 scanner heads facing forward and to the rear of the vehicle in a crossing pattern. The laser captures 3D points at a point density along the ground of approximately 0.001 feet at speeds up to 70mph. This scanner can be adjusted to scan at a rate that is applicable for the project specifications to limit the amount of data collected and to ensure that the resulting point cloud data is manageable. Right-of-Way imagery is also co-collected along with this LiDAR point cloud data. These images are used to identify appropriate attribution for each feature type being collected. They are also used to identify the real-world features that are measured and the exact location of the minimum vertical clearance for the Bridge or Overhead structure. The following graphic illustrates these concepts.

Dual Head Scanners – One-Pass Technology

Dense Point Clouds for Precise Measurements

High-Resolution Right-of-Way Imagery is Used to Identify Clearance Structure for Measurement

LiDAR Point Cloud of Same Overhead Structure with Clearance Measurements

Right-of-Way Imagery Fused with LiDAR Point Cloud for Photo-Realistic View

Bridge Clearance Measurements (LiDAR Intensity View)

Bridge Clearance Measurements (LiDAR Fusion View)

Local Orthophotography and LiDAR data co-registered to support the data extraction process

Google Earth is used as a reference during compilation to verify bridge location and layout.

Once the data has been captured in the field, it is post-processed back in the office using a semi-automated approach. The Overhead Structure or bridge is classified in the point cloud using a manual process. The overhead points are classified into an “Overhead/Bridge” class. Then, the software automates the analysis of finding the lowest clearance point for a column of the data set.

Bridge Structures Illustrated in Point Clouds

For example, the user can set a preference to search a radius of 1-foot and then the software will automatically find the closest ground point corresponding to the column of data. The minimum clearance value will be identified and recorded in the software for that column of data. This process is automatically repeated for the remainder of the structure until the minimum clearance point has been identified and located in the point cloud. The user can specify the output of the data as either a single minimum clearance of that structure, or can identify the lowest point vertically along a horizontal distribution of measurements. An example of this would be to return the lowest point per lane across a roadway for a particular structure. In conclusion, mobile LiDAR and Right-of-Way imagery are a safe and accurate way to measure the horizontal and vertical clearance of overhead and bridge structures. This methodology promotes a safe working environment for both the DOT worked and the traveling public. It is also a cost-effective way to collect large amounts of 3D point cloud data and process it efficiently as it is applied on a per-structure basis.